The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 11, 2018

Filed:

Nov. 23, 2016
Applicant:

General Electric Company, Schenectady, NY (US);

Inventors:

Jiang Hsieh, Waukesha, WI (US);

Gopal Avinash, San Ramon, CA (US);

Saad Sirohey, Pewaukee, WI (US);

Xin Wang, Clifton Park, NY (US);

Zhye Yin, Schenectady, NY (US);

Bruno De Man, Niskayuna, NY (US);

Assignee:

General Electric Company, Schenectady, NY (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06K 9/62 (2006.01); G06N 3/04 (2006.01); G06N 3/08 (2006.01); G06T 7/00 (2017.01); G06K 9/46 (2006.01);
U.S. Cl.
CPC ...
G06K 9/6265 (2013.01); G06K 9/4604 (2013.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G06T 7/0012 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10104 (2013.01); G06T 2207/10108 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/30168 (2013.01);
Abstract

Methods and apparatus to automatically generate an image quality metric for an image are provided. An example method includes automatically processing a first medical image using a deployed learning network model to generate an image quality metric for the first medical image, the deployed learning network model generated from a digital learning and improvement factory including a training network, wherein the training network is tuned using a set of labeled reference medical images of a plurality of image types, and wherein a label associated with each of the labeled reference medical images indicates a central tendency metric associated with image quality of the image. The example method includes computing the image quality metric associated with the first medical image using the deployed learning network model by leveraging labels and associated central tendency metrics to determine the associated image quality metric for the first medical image.


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